Learning Pathway for Business Intelligence Professionals

The program is structured to take students from foundational concepts to advanced application, ensuring a comprehensive understanding of Business Intelligence (BI).

Breakdown of Tuition Fees and Discounts

The tuition fee for the 3-month (12-week) program is $1,500 USD.
Application Fee: $100 USD (Note: Payment of this fee is compulsory, discounts do not cover it.)

INVESTMENT HOURS

A student needs to invest a total of 72 hours in the 3-month program.
The breakdown of the calculation:

The course is divided into four main phases:

  1. Foundational
  2. Core Skills
  3. Advanced Application
  4. Project/Portfolio

    Phase 1: Foundational BI Concepts (Weeks 1-3)

    This phase introduces the core principles and tools of Business Intelligence.

  1. Week 1: Introduction to Business Intelligence
    • What is BI?
    • The role of BI in modern business.
    • Data types and sources.
    • The BI lifecycle.
  2. Week 2: Data Fundamentals & SQL
    • Introduction to relational databases.
    • Fundamentals of SQL (Structured Query Language).
    • Writing basic queries (SELECT, FROM, WHERE).
  3. Week 3: Data Warehousing & ETL
    • Concepts of data warehousing.
    • Introduction to ETL (Extract, Transform, Load) processes.
    • Data governance and quality.

    Phase 2: Core BI Skills & Tools (Weeks 4-6)

    This phase focuses on practical skills using industry-standard tools.

  4. Week 4: Data Visualization with Tableau/Power BI
    • Introduction to data visualization principles.
    • Connecting to data sources.
    • Creating basic charts and graphs.
  5. Week 5: Advanced Data Visualization
    • Building interactive dashboards.
    • Using filters, parameters, and actions.
    • Storytelling with data.
  6. Week 6: Excel for Business Analysis
    • Advanced Excel functions for data analysis (PivotTables, VLOOKUP, INDEX/MATCH).
    • Introduction to Power Query for data cleaning and transformation.

    Phase 3: Advanced BI Applications (Weeks 7-9)

    This phase delves into more complex BI techniques and predictive analytics.

  7. Week 7: Statistical Analysis for BI
    • Basic statistical concepts (mean, median, mode).
    • Correlation and regression analysis.
    • Interpreting statistical results.
  8. Week 8: Introduction to Predictive Analytics
    • What is predictive analytics?
    • Simple forecasting models.
    • Machine learning concepts for business.
  9. Week 9: Data Security & Ethics
    • Data privacy regulations (e.g., GDPR, CCPA).
    • Ethical considerations in data analysis.
    • Ensuring data security in BI environments.

    Phase 4: Project & Portfolio Development (Weeks 10-12)

    The final phase focuses on synthesizing knowledge into a practical project.

  10. Week 10: Project Scoping & Data Collection
    • Defining a business problem.
    • Identifying and collecting relevant data.
    • Data cleaning and preparation.
  11. Week 11: Project Execution & Dashboard Creation
    • Applying learned BI skills to the project dataset.
    • Developing a comprehensive BI dashboard.
  12. Week 12: Final Presentation & Career Preparation
    • Presenting the final project to peers and instructors.
    • Building a professional BI portfolio.
    • Tips for BI career interviews.